code: def test_1m_0cf_wgt_metric_dict(metric_fn):
      target = MetricFrame(
          metrics={metric_fn.__name__: metric_fn},
          y_true=y_t,
          y_pred=y_p,
          sensitive_features=g_1,  # Unused for overall
          sample_params={metric_fn.__name__: {"sample_weight": s_w}},
      )
      assert target._user_supplied_callable is False
  
      # Check user visible
      expected = metric_fn(y_t, y_p, sample_weight=s_w)
      assert isinstance(target.overall, pd.Series)
      assert len(target.overall) == 1
      assert target.overall[metric_fn.__name__] == expected
  
file_path: fairlearn/test/unit/metrics/test_metricframe_overall.py
imports: import numpy
  import pandas
  import pytest
  import sklearn.metrics
  from fairlearn.metrics import MetricFrame
  from .data_for_test import g_1, g_2, g_3, s_w, y_p, y_t
label_desc: Use image node_id 4 for calling a global function with example usage: test_1m_0cf_wgt_metric_dict(metric_fn) without return types